Interpretation and Identification of Tourism Sector Clustering
- 10.2991/aebmr.k.200312.246How to use a DOI?
The question of identifying the clustering of the tourist sector due to its positive impact on the economic development of Russia was considered. The author’s methodological approach to the assessment of identification based on the integral method was presented. This approach includes six groups of indicators: assessments of natural and resource potential of a recreational area, localization, specialization, per head production, heterogeneity, and the competitiveness of the tourist sector in the region. Each group of the indicators includes single indicators; it should be noted that for the assessment of the natural and resource potential of a recreational area expert method is used with follow-on use of integral method to determine the resulting indicator. For the remaining groups of indicators, only the integral method is used. For the final conclusions on the identification of clustering of the tourist sector, the authors developed a scale with interval estimates and a presentation of the characteristics of each of them. Approbation of the author’s methodological approach was carried out using the example of the tourist sector of the Republic of Crimea with a test of objectivity by the Pearson criterion. The results indicate that there are good opportunities for the creation and development of tourist clusters in the regions of Crimea: south-coastal, south-western and southeast regions have a high level of clustering of the tourist sector; western and eastern regions have a good level, and central region has an average level.
- © 2020, the Authors. Published by Atlantis Press.
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Cite this article
TY - CONF AU - A I Pashentsev AU - A A Garmider PY - 2020 DA - 2020/03/17 TI - Interpretation and Identification of Tourism Sector Clustering BT - Proceedings of the International Scientific Conference "Far East Con" (ISCFEC 2020) PB - Atlantis Press SP - 1780 EP - 1786 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.200312.246 DO - 10.2991/aebmr.k.200312.246 ID - Pashentsev2020 ER -